Georgia Tech, CS 7545 Machine Learning Theory,
Fall 2013

MACHINE LEARNING THEORY

Course description: Machine learning studies automatic
methods for learning to make accurate predictions or useful
decisions based on past observations and experience, and it has
become a highly successful discipline with applications in many
areas such as natural language processing, speech recognition,
computer vision, or gene discovery. This course on the design and
theoretical analysis of machine learning methods will cover a broad
range of important problems studied in theoretical machine learning.
It will provide a basic arsenal of powerful mathematical tools for
their analysis, focusing on both statistical and computational
aspects. We will examine questions such as "What guarantees can we
prove on the performance of learning algorithms? " and "What can we
say about the inherent ease or difficulty of learning problems?". In
addressing these and related questions we will make connections to
statistics, algorithms, complexity theory, information theory, game
theory, and empirical machine learning research. You can find more
info here.